Marine predators algorithm for parameters estimation of photovoltaic modules considering various weather conditions

Marine Predators Algorithm: A Review

“…Modified MPA Introduced a novel population-based MPA to restructure the PV array dynamically [174] Photovoltaic (PV) module Original MPA A new method of the MPA to properly extract the electrical parameters of the TDPV model of a PV panel [143] Power dispatch problem Hybrid MPA MPA hybrid with the PSO to improve local search operators to emphasize the local search capabilities of the MPA and obtain a better local optimum for the power dispatch problem [139] Photovoltaic system Hybrid MPA Presented a hybrid version of MPA based on an opposition-based learning strategy and the global maximum power point of the photovoltaic system problem [87] Photovoltaic system Original MPA A novel proposed photovoltaic model based on MPA to estimate the optimal model parameters of solar cells or modules [136] PV/DG/Battery System Modified MPA Proposed a new version of the MPA by introducing an adaptive learning factor to enhance the updating behaviour of the search agents near prey and improve convergence toward optimal solutions [181] Solar photovoltaic Hybrid MPA A hybrid version of MPA is proposed to enhance the MPA searching behaviour, skipping local optima, and balancing local and global search [122] Photovoltaic system Hybrid MPA The primary aim of proposing such an approach is to employ the slime mould algorithm with the local search operators of the MPA to lead the search agents to exploit the search space better and find the optimal solution [176] Energy…”

An Efficient Electric Charged Particles Optimization Algorithm for Numerical Optimization and Optimal Estimation of Photovoltaic Models

“…The objective function is to extract the best parameter values of the PV models by reducing the variance between the estimated data and the measured data. The objective function of SDM, DDM, and TDM is given as follows [33]:…”

“…The flower pollination algorithms (FPA) were used to extract the global parameters of both the single-diode and the double-diode models based on the experimental data [15]. Additionally, other recent optimization algorithms were used to find the best values of PV parameters, including transient search optimization (TSO) [16], cuckoo search (CS) [17], whale optimization algorithm (WOA) [18], supply demand-based optimization (SDO) [19], salp swarm algorithm (SSA) [20], improved bonobo optimizer (IBO) [21], multiverse optimizer (MVO) [22], tree growth algorithm (TGA) [23], grey wolf optimization (GWO) [24], triple-phase teaching-learning-based optimization (TPTLBO) [25], ant lion optimization (ALO) [26], chaos game optimization (CGO) [27], Harris hawk optimization (HHO) [28], Rao algorithm [29], slime mould algorithm (SMA) [30], and hybrid techniques, such as hybrid adaptive TLBO with DE algorithm (ATLDE) [31], GWOCS [1], PSOGWO [32], Marine predator algorithm (MPA) [33], Coyote optimization [34], and Jaya algorithm and its variants [35]. Each technique has various strategies to achieve a certain objective, and the power of each technique depends on the precision of the estimated parameters, computation time, and computational complexity.…”

An efficient capuchin search algorithm for extracting the parameters of different PV cells/modules

“…The PV cells are used to convert the solar radiation into direct electrical energy. The PV generating units are widely used in different applications, such as standalone, microgrids, and large grids with other generating units (Ibrahim et al, 2020;Jiao et al, 2020;Ginidi et al, 2021;Sattar et al, 2021). The PV panels consist of many cells that are connected to each other in series and parallel to obtain the current and voltage required, and the performance of the solar cell is affected by the change in temperature and the intensity of solar radiation (Long et al, 2021).…”